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1
DEBBAL, S. M., and F. BEREKSI-REGUIG. "COMPARISON BETWEEN DISCRETE AND PACKET WAVELET TRANSFORM ANALYSES IN THE STUDY OF HEARTBEAT CARDIAC SOUNDS." Journal of Mechanics in Medicine and Biology 07, no. 02 (June 2007): 199–214. http://dx.doi.org/10.1142/s021951940700225x.
Повний текст джерелаАнотація:
This work investigates the study of heartbeat cardiac sounds through time–frequency analysis by using the wavelet transform method. Heart sounds can be utilized more efficiently by medical doctors when they are displayed visually rather through a conventional stethoscope. Heart sounds provide clinicians with valuable diagnostic and prognostic information. Although heart sound analysis by auscultation is convenient as a clinical tool, heart sound signals are so complex and nonstationary that they are very difficult to analyze in the time or frequency domain. We have studied the extraction of features from heart sounds in the time–frequency (TF) domain for the recognition of heart sounds through TF analysis. The application of wavelet transform (WT) for heart sounds is thus described. The performances of discrete wavelet transform (DWT) and wavelet packet transform (WP) are discussed in this paper. After these transformations, we can compare normal and abnormal heart sounds to verify the clinical usefulness of our extraction methods for the recognition of heart sounds.
2
Andrisevic, Nicholas, Khaled Ejaz, Fernando Rios-Gutierrez, Rocio Alba-Flores, Glenn Nordehn, and Stanley Burns. "Detection of Heart Murmurs Using Wavelet Analysis and Artificial Neural Networks." Journal of Biomechanical Engineering 127, no. 6 (July 8, 2005): 899–904. http://dx.doi.org/10.1115/1.2049327.
Повний текст джерелаАнотація:
This paper presents the algorithm and technical aspects of an intelligent diagnostic system for the detection of heart murmurs. The purpose of this research is to address the lack of effectively accurate cardiac auscultation present at the primary care physician office by development of an algorithm capable of operating within the hectic environment of the primary care office. The proposed algorithm consists of three main stages. First; denoising of input data (digital recordings of heart sounds), via Wavelet Packet Analysis. Second; input vector preparation through the use of Principal Component Analysis and block processing. Third; classification of the heart sound using an Artificial Neural Network. Initial testing revealed the intelligent diagnostic system can differentiate between normal healthy heart sounds and abnormal heart sounds (e.g., murmurs), with a specificity of 70.5% and a sensitivity of 64.7%.
3
Adiban, Mohammad, Bagher BabaAli, and Saeedreza Shehnepoor. "Statistical feature embedding for heart sound classification." Journal of Electrical Engineering 70, no. 4 (August 1, 2019): 259–72. http://dx.doi.org/10.2478/jee-2019-0056.
Повний текст джерелаАнотація:
Abstract Cardiovascular Disease (CVD) is considered as one of the principal causes of death in the world. Over recent years, this field of study has attracted researchers’ attention to investigate heart sounds’ patterns for disease diagnostics. In this study, an approach is proposed for normal/abnormal heart sound classification on the Physionet challenge 2016 dataset. For the first time, a fixed length feature vector; called i-vector; is extracted from each heart sound using Mel Frequency Cepstral Coefficient (MFCC) features. Afterwards, Principal Component Analysis (PCA) transform and Variational Autoencoder (VAE) are applied on the i-vector to achieve dimension reduction. Eventually, the reduced size vector is fed to Gaussian Mixture Models (GMMs) and Support Vector Machine (SVM) for classification purpose. Experimental results demonstrate the proposed method could achieve a performance improvement of 16% based on Modified Accuracy (MAcc) compared with the baseline system on the Physionet2016 dataset.
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Li, Suyi, Feng Li, Shijie Tang, and Wenji Xiong. "A Review of Computer-Aided Heart Sound Detection Techniques." BioMed Research International 2020 (January 10, 2020): 1–10. http://dx.doi.org/10.1155/2020/5846191.
Повний текст джерелаАнотація:
Cardiovascular diseases have become one of the most prevalent threats to human health throughout the world. As a noninvasive assistant diagnostic tool, the heart sound detection techniques play an important role in the prediction of cardiovascular diseases. In this paper, the latest development of the computer-aided heart sound detection techniques over the last five years has been reviewed. There are mainly the following aspects: the theories of heart sounds and the relationship between heart sounds and cardiovascular diseases; the key technologies used in the processing and analysis of heart sound signals, including denoising, segmentation, feature extraction and classification; with emphasis, the applications of deep learning algorithm in heart sound processing. In the end, some areas for future research in computer-aided heart sound detection techniques are explored, hoping to provide reference to the prediction of cardiovascular diseases.
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Giordano, Noemi, and Marco Knaflitz. "A Novel Method for Measuring the Timing of Heart Sound Components through Digital Phonocardiography." Sensors 19, no. 8 (April 19, 2019): 1868. http://dx.doi.org/10.3390/s19081868.
Повний текст джерелаАнотація:
The auscultation of heart sounds has been for decades a fundamental diagnostic tool in clinical practice. Higher effectiveness can be achieved by recording the corresponding biomedical signal, namely the phonocardiographic signal, and processing it by means of traditional signal processing techniques. An unavoidable processing step is the heart sound segmentation, which is still a challenging task from a technical viewpoint—a limitation of state-of-the-art approaches is the unavailability of trustworthy techniques for the detection of heart sound components. The aim of this work is to design a reliable algorithm for the identification and the classification of heart sounds’ main components. The proposed methodology was tested on a sample population of 24 healthy subjects over 10-min-long simultaneous electrocardiographic and phonocardiographic recordings and it was found capable of correctly detecting and classifying an average of 99.2% of the heart sounds along with their components. Moreover, the delay of each component with respect to the corresponding R-wave peak and the delay among the components of the same heart sound were computed: the resulting experimental values are coherent with what is expected from the literature and what was obtained by other studies.
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Boulares, Mehrez, Reem Alotaibi, Amal AlMansour, and Ahmed Barnawi. "Cardiovascular Disease Recognition Based on Heartbeat Segmentation and Selection Process." International Journal of Environmental Research and Public Health 18, no. 20 (October 18, 2021): 10952. http://dx.doi.org/10.3390/ijerph182010952.
Повний текст джерелаАнотація:
Assessment of heart sounds which are generated by the beating heart and the resultant blood flow through it provides a valuable tool for cardiovascular disease (CVD) diagnostics. The cardiac auscultation using the classical stethoscope phonological cardiogram is known as the most famous exam method to detect heart anomalies. This exam requires a qualified cardiologist, who relies on the cardiac cycle vibration sound (heart muscle contractions and valves closure) to detect abnormalities in the heart during the pumping action. Phonocardiogram (PCG) signal represents the recording of sounds and murmurs resulting from the heart auscultation, typically with a stethoscope, as a part of medical diagnosis. For the sake of helping physicians in a clinical environment, a range of artificial intelligence methods was proposed to automatically analyze PCG signal to help in the preliminary diagnosis of different heart diseases. The aim of this research paper is providing an accurate CVD recognition model based on unsupervised and supervised machine learning methods relayed on convolutional neural network (CNN). The proposed approach is evaluated on heart sound signals from the well-known, publicly available PASCAL and PhysioNet datasets. Experimental results show that the heart cycle segmentation and segment selection processes have a direct impact on the validation accuracy, sensitivity (TPR), precision (PPV), and specificity (TNR). Based on PASCAL dataset, we obtained encouraging classification results with overall accuracy 0.87, overall precision 0.81, and overall sensitivity 0.83. Concerning Micro classification results, we obtained Micro accuracy 0.91, Micro sensitivity 0.83, Micro precision 0.84, and Micro specificity 0.92. Using PhysioNet dataset, we achieved very good results: 0.97 accuracy, 0.946 sensitivity, 0.944 precision, and 0.946 specificity.
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Omari, Tahar, and Fethi Bereksi-Reguig. "An automatic wavelet denoising scheme for heart sounds." International Journal of Wavelets, Multiresolution and Information Processing 13, no. 03 (May 2015): 1550016. http://dx.doi.org/10.1142/s0219691315500162.
Повний текст джерелаАнотація:
Phonocardiograms (PCGs), recording of heart sounds, have many advantages over traditional auscultation in that they may be replayed and analyzed for spectral and frequency information. PCG is not a widely used diagnostic tool as it could be. One of the major problems with PCG is noise corruption. Many sources of noise may pollute a PCG signal including lung and breath sounds, environmental noise and blood flow noises which are known as murmurs. These murmurs contain many information on heart hemodynamic which can be used particularly in detecting of heart valve diseases. An automated system for heart murmurs processing can be an important tool in diagnostic of heart diseases using a simple electronic stethoscope. However, the first step before developing any automated system is the segmentation of the PCG signals from which the murmurs can be separated. A robust segmentation algorithm must have a robust denoising technique, where, wavelet transform (WT) is among the ones which exhibits very high satisfactory results in such situations. However, the selection of level of decomposition and the mother wavelet are the major challenges. This paper proposes a novel approach for an automatic selection of mother wavelet and level of decomposition that can be used in heart sounds denoising. The obtained results on both simulative and real PCG signals showed that the proposed approach can successfully select the best level of decomposition with the best mother wavelet that can be used in extraction operation of main PCG sound components (S1 and S2) from various types of murmurs.
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Bourouhou, Abdelhamid, Abdelilah Jilbab, Chafik Nacir, and Ahmed Hammouch. "Heart Sounds Classification for a Medical Diagnostic Assistance." International Journal of Online and Biomedical Engineering (iJOE) 15, no. 11 (July 16, 2019): 88. http://dx.doi.org/10.3991/ijoe.v15i11.10804.
Повний текст джерелаАнотація:
<span lang="EN-US">In order to develop the assessment of phonocardiogram “PCG” signal for discrimination between two of people classes – individuals with heart disease and healthy one- we have adopted the database provided by "The PhysioNet/Computing in Cardilogy Challenge 2016", which contains records of heart sounds 'PCG '. This database is chosen in order to compare and validate our results with those already published. We subsequently extracted 20 features from each provided record. For classification, we used the Generalized Linear Model (GLM), and the Support Vector Machines (SVMs) with its different types of kernels (i.e.; Linear, polynomial and MLP). The best classification accuracy obtained was 88.25%, using the SVM classifier with an MLP kernel.</span>
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Larsen, Bjarke Skogstad, Simon Winther, Louise Nissen, Axel Diederichsen, Morten Bøttcher, Johannes Jan Struijk, Mads Græsbøll Christensen, and Samuel Emil Schmidt. "Spectral analysis of heart sounds associated with coronary artery disease." Physiological Measurement 42, no. 10 (October 1, 2021): 105013. http://dx.doi.org/10.1088/1361-6579/ac2fb7.
Повний текст джерелаАнотація:
Abstract Objective. The aim of this study was to find spectral differences of diagnostic interest in heart sound recordings of patients with coronary artery disease (CAD) and healthy subjects. Approach. Heart sound recordings from three studies were pooled, and patients with clear diagnostic outcomes (positive: CAD and negative: Non-CAD) were selected for further analysis. Recordings from 1146 patients (191 CAD and 955 Non-CAD) were analyzed for spectral differences between the two groups using Welch’s spectral density estimate. Frequency spectra were estimated for systole and diastole segments, and time-frequency spectra were estimated for first (S1) and second (S2) heart sound segments. An ANCOVA model with terms for diagnosis, age, gender, and body mass index was used to evaluate statistical significance of the diagnosis term for each time-frequency component. Main results. Diastole and systole segments of CAD patients showed increased energy at frequencies 20–120 Hz; furthermore, this difference was statistically significant for the diastole. CAD patients showed decreased energy for the mid-S1 and mid-S2 segments and conversely increased energy before and after the valve sounds. Both S1 and S2 segments showed regions of statistically significant difference in the time-frequency spectra. Significance. Results from analysis of the diastole support findings of increased low-frequency energy from previous studies. Time-frequency components of S1 and S2 sounds showed that these two segments likely contain heretofore untapped information for risk assessment of CAD using phonocardiography; this should be considered in future works. Further development of features that build on these findings could lead to improved acoustic detection of CAD.
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Ms. Mohini Dadhe, Ms. Sneha Miskin. "Optimized Wireless Stethoscope Using Butterworth Filter." International Journal of New Practices in Management and Engineering 4, no. 03 (September 30, 2015): 01–05. http://dx.doi.org/10.17762/ijnpme.v4i03.37.
Повний текст джерелаАнотація:
Acoustic stethoscope is a primary diagnostic tool used by doctors for effective analysis of various diseases. But, it suffers defects such as low level heart sounds and presence of murmurs. This project aims at developing ‘Noise removal in stethoscope using Butterworth filter’. In this, the low level heart sounds were amplified with high gain pre-amplifier circuit. A review of basic filters like low pass RC filter, Butterworth filter, Chebyshev filter and Bessel filter are done for elimination of murmurs and best suited filter is suggested. Finally, amplified noise free heart sounds are simulated using Proteus 7.4. The results prove that efficient filter for designing is ‘Butterworth filter’.
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Soto-Murillo, Manuel A., Jorge I. Galván-Tejada, Carlos E. Galván-Tejada, Jose M. Celaya-Padilla, Huizilopoztli Luna-García, Rafael Magallanes-Quintanar, Tania A. Gutiérrez-García, and Hamurabi Gamboa-Rosales. "Automatic Evaluation of Heart Condition According to the Sounds Emitted and Implementing Six Classification Methods." Healthcare 9, no. 3 (March 12, 2021): 317. http://dx.doi.org/10.3390/healthcare9030317.
Повний текст джерелаАнотація:
The main cause of death in Mexico and the world is heart disease, and it will continue to lead the death rate in the next decade according to data from the World Health Organization (WHO) and the National Institute of Statistics and Geography (INEGI). Therefore, the objective of this work is to implement, compare and evaluate machine learning algorithms that are capable of classifying normal and abnormal heart sounds. Three different sounds were analyzed in this study; normal heart sounds, heart murmur sounds and extra systolic sounds, which were labeled as healthy sounds (normal sounds) and unhealthy sounds (murmur and extra systolic sounds). From these sounds, fifty-two features were calculated to create a numerical dataset; thirty-six statistical features, eight Linear Predictive Coding (LPC) coefficients and eight Cepstral Frequency-Mel Coefficients (MFCC). From this dataset two more were created; one normalized and one standardized. These datasets were analyzed with six classifiers: k-Nearest Neighbors, Naive Bayes, Decision Trees, Logistic Regression, Support Vector Machine and Artificial Neural Networks, all of them were evaluated with six metrics: accuracy, specificity, sensitivity, ROC curve, precision and F1-score, respectively. The performances of all the models were statistically significant, but the models that performed best for this problem were logistic regression for the standardized data set, with a specificity of 0.7500 and a ROC curve of 0.8405, logistic regression for the normalized data set, with a specificity of 0.7083 and a ROC curve of 0.8407, and Support Vector Machine with a lineal kernel for the non-normalized data; with a specificity of 0.6842 and a ROC curve of 0.7703. Both of these metrics are of utmost importance in evaluating the performance of computer-assisted diagnostic systems.
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Bourouhou, Abdelhamid, Abdelilah Jilbab, Chafik Nacir, and Ahmed Hammouch. "Heart Sound Signals Segmentation and Multiclass Classification." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 15 (December 15, 2020): 64. http://dx.doi.org/10.3991/ijoe.v16i15.16817.
Повний текст джерелаАнотація:
<em>The heart is the organ that pumps blood with oxygen and nutrients into all body organs by a rhythmic cycle overlapping between contraction and dilatation. This is done by producing an audible sound which we can hear using a stethoscope. Many are the causes affecting the normal function of this most vital organ. In this respect, the heart sound classification has become one of the diagnostic tools that allow the discrimination between patients and healthy people; this diagnosis is less painful, less costly and less time consuming. In this paper, we present a classification algorithm based on the extraction of 20 features from segmented phonocardiogram “PCG” signals. We applied four types of machine learning classifiers that are k- Near Neighbor “KNN”, Support Vector Machine “SVM”, Tree, and Naïve Bayes “NB” so as to train old features and predict the new entry. To make our results measurable, we have chosen the PASCAL Classifying Heart Sounds challenge, which is a rich database and is conducive to classifying the PCGs into four classes for dataset A and three classes for dataset B. The main finding is about 3.06 total precision of the dataset A and 2.37 of the dataset B.</em>
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Collins, S. P. "Combination of Brain Natriuretic Peptide and Automated Heart Sounds Improves Heart Failure Diagnostic Accuracy." Academic Emergency Medicine 12, Supplement 1 (May 1, 2005): 97. http://dx.doi.org/10.1197/j.aem.2005.03.271.
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Güven, Mesut, Fırat Hardalaç, Kanat Özışık, and Funda Tuna. "Heart Diseases Diagnose via Mobile Application." Applied Sciences 11, no. 5 (March 9, 2021): 2430. http://dx.doi.org/10.3390/app11052430.
Повний текст джерелаАнотація:
One of the oldest and most common methods of diagnosing heart abnormalities is auscultation. Even for experienced medical doctors, it is not an easy task to detect abnormal patterns in the heart sounds. Most digital stethoscopes are now capable of recording and transferring heart sounds. Moreover, it is proven that auscultation records can be classified as healthy or unhealthy via artificial intelligence techniques. In this work, an artificial intelligence-powered mobile application that works in a connectionless fashion is presented. According to the clinical experiments, the mobile application can detect heart abnormalities with approximately 92% accuracy, which is comparable to if not better than humans since only a small number of well-trained cardiologists can analyze auscultation records better than artificial intelligence. Using the diagnostic ability of artificial intelligence in a mobile application would change the classical way of auscultation for heart disease diagnosis.
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Joseph, Anthony, Radek Martinek, Radana Kahankova, Rene Jaros, Jan Nedoma, and Marcel Fajkus. "Simulator of Foetal Phonocardiographic Recordings and Foetal Heart Rate Calculator." Journal of Biomimetics, Biomaterials and Biomedical Engineering 39 (November 2018): 57–64. http://dx.doi.org/10.4028/www.scientific.net/jbbbe.39.57.
Повний текст джерелаАнотація:
Nowadays, the classic diagnostic method to monitor general foetus well-being using the foetal heart rate conditions, ultrasonic cardiotography, is called into question. A valuable alternative is foetal phonocardiography, a passive and low-cost recording of foetal heart sounds. This paper presents a software which generates synthetic foetal phonocardiographic recordings simulating different recording conditions (by modifying noise level). From a real foetal phonocardiographic recording this software calculates the foetal heart rate. The software was developed using information picked from the literature especially for identifying the waveforms and characteristics of foetal and maternal heart sounds, and the different noises involved in real phonocardiographic recordings. Considering the possibility to simulate different recording situations and physiological or pathological foetal conditions just by modifying some parameters, this simulator software can be useful for testing different foetal-heart-rate extraction algorithms, like the authors’ one. In this paper are presented the different postulates used for developing this software.
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Kobat, Mehmet Ali, Tarik Kivrak, Prabal Datta Barua, Turker Tuncer, Sengul Dogan, Ru-San Tan, Edward J. Ciaccio, and U. Rajendra Acharya. "Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds." Diagnostics 11, no. 11 (October 22, 2021): 1962. http://dx.doi.org/10.3390/diagnostics11111962.
Повний текст джерелаАнотація:
COVID-19 and heart failure (HF) are common disorders and although they share some similar symptoms, they require different treatments. Accurate diagnosis of these disorders is crucial for disease management, including patient isolation to curb infection spread of COVID-19. In this work, we aim to develop a computer-aided diagnostic system that can accurately differentiate these three classes (normal, COVID-19 and HF) using cough sounds. A novel handcrafted model was used to classify COVID-19 vs. healthy (Case 1), HF vs. healthy (Case 2) and COVID-19 vs. HF vs. healthy (Case 3) automatically using deoxyribonucleic acid (DNA) patterns. The model was developed using the cough sounds collected from 241 COVID-19 patients, 244 HF patients, and 247 healthy subjects using a hand phone. To the best our knowledge, this is the first work to automatically classify healthy subjects, HF and COVID-19 patients using cough sounds signals. Our proposed model comprises a graph-based local feature generator (DNA pattern), an iterative maximum relevance minimum redundancy (ImRMR) iterative feature selector, with classification using the k-nearest neighbor classifier. Our proposed model attained an accuracy of 100.0%, 99.38%, and 99.49% for Case 1, Case 2, and Case 3, respectively. The developed system is completely automated and economical, and can be utilized to accurately detect COVID-19 versus HF using cough sounds.
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Shariat Panah, Davoud, Andrew Hines, Joseph A. McKeever, and Susan McKeever. "An audio processing pipeline for acquiring diagnostic quality heart sounds via mobile phone." Computers in Biology and Medicine 145 (June 2022): 105415. http://dx.doi.org/10.1016/j.compbiomed.2022.105415.
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Venkatesan, M., M. Saravanan, B. Gowri, P. Selvaraj, S. Senthilkumar, P. Thamizhmagan, S. Yogeshpriya, and K. Jayalakshmi. "Ultrasound and Radiographic Imaging Diagnosis of Diaphragmatic Hernia in a Transition Cow: A Case Report." INDIAN JOURNAL OF VETERINARY SCIENCES AND BIOTECHNOLOGY 15, no. 03 (March 9, 2020): 77–78. http://dx.doi.org/10.21887/ijvsbt.15.3.21.
Повний текст джерелаАнотація:
A four and half-year-old recently calved cross breed Jersey cow was presented with the clinical signs of anorexia, recurrent bloat, bruxism and not voided dung for the past one week. Clinical examination revealed congested mucous membrane, sunken eyeball, and severely distended lower abdomen; clinically, bloat was evident. On Auscultation of heart at 4th intercoastal space, low-intensity heart sounds were heard. Rectal examination revealed scanty foul-smelling dung with blood tinge. In an attempt to relieve the bloat rumen stomach was intubated, which failed to relieve the gas. The clinical suspicion pointed to the possibility of foreign body syndrome. Hence radiography was done by keeping the animal in standing position; however it revealed no clear contour of heart, reticulum, and diaphragm; another attempt was made, wherein the animal was cast on right lateral recumbency and radiography was done at 90-100 kVp, 50-60 mAs and a focus film distance of 90-100 cm using an 800 mA X-ray machine. As we would not get any diagnostic confirmation findings in radiography, an ultrasonographic assessment was planned. Ultrasonography was done with (Esoate Mylab 1) 2.5. to 5 MHz curvy linear transducer. Ultrasound examination of the heart (Venkatesan et al., 2019) and reticulum (Braun et al., 1993) was done at the left side between 4th to 5th intercostal space of thoracic cavity using the window between 6th to 8th intercoastal in the abdominal cavity. Physical examination revealed a dull and depressed animal; distended left flank, moderate dehydration, elevated rectal temperature (40°C), low-intensity heart sounds with a normal heart rate was observed. Hematology was unremarkable; smear study was negative for blood parasites.
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HRIBAN, Alexandra-Ioana, Daniela CRISU, Manuela URSARU, Laurentiu SORODOC, and Catalina LIONTE. "An Uncommon Congenital Abnormality Discovered Using Multimodality Cardiac Imaging in an Elder Hospitalized For Decompensated Heart Failure." Romanian Journal of Cardiology 31, no. 3 (September 24, 2021): 627–32. http://dx.doi.org/10.47803/rjc.2021.31.3.627.
Повний текст джерелаАнотація:
We report the case of a 77-year-old patient admitted for worsening dyspnea, palpitations and dizziness. The electrocardiogram (ECG) showed atrial fibrillation (AF) and left bundle branch block (LBBB). Clinical examination showed hypoxemia (SaO2 87% room air), jugular venous distension, pitting edema, arrhythmic heart sounds, a splitting of the second heart sound and systolic murmur (III-IV/VI) in the tricuspid area. Transthoracic echocardiography (TTE) showed right heart dilation, moderate tricuspid regurgitation, biventricular hypertrophy, and a dilated coronary sinus (CS). Agitated saline injection in the left basilar vein raised a suspicion of persistent left superior vena cava (PLSVC) to coronary sinus fistula. Transesophgaeal ecocardiography (TOE) showed a superior sinus venosus defect, with bidirectional shunt, and persistence of LSVC. CT angiography confirmed and detalied the malformation features. A low suspicion for congenital defects in older adults presents a significant diagnostic challenge. Multimodality cardiac imaging is critical in determining the etiology of right heart dilation, and knowledge of the anatomy and physiology of various shunt lesions is essential for clinicians.
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Choi, Hee Joung. "Evaluation and diagnostic approach for heart murmurs in children." Journal of the Korean Medical Association 63, no. 7 (July 10, 2020): 398–403. http://dx.doi.org/10.5124/jkma.2020.63.7.398.
Повний текст джерелаАнотація:
Heart murmurs are common in children. Most of them are innocent murmurs with normal heart anatomy and function, and only a few are pathologic murmurs with congenital heart anomaly or abnormal heart function. However, a heart murmur may be the sole symptom of serious heart disease. Therefore, careful evaluation of heart murmurs for distinguishing pathologic murmurs from innocent murmurs is important. Heart murmurs are described by their intensity, timing in the cardiac cycle, location, transmission, and quality. Murmurs, such as a holosystolic or diastolic murmur, of grade 3 or higher intensity, harsh quality, an abnormal S2, a systolic click, or increased intensity when the patient stands are more likely to be pathologic murmurs. Innocent murmurs are more likely to be systolic murmurs, with soft sounds, short duration, low pitch, and varying intensity with phases of respiration and posture (disappears with standing). Not only auscultation but also physical examination findings are important to evaluate heart murmurs. The gold standard test for the evaluation of any potentially pathologic murmur is echocardiography. For the appropriate use of echocardiography, close physical examination, including auscultation, is essential and requires considerable practice.
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Otto, Sven, and Robert Höpfner. "The Rare Occurrence of a Left Atrial Thrombus in a Dog." Case Reports in Veterinary Medicine 2020 (October 22, 2020): 1–5. http://dx.doi.org/10.1155/2020/8848627.
Повний текст джерелаАнотація:
Intracardiac thrombi are rare in dogs. If they occur, they are mostly seen in the right atrium while only two case reports describing a mural left atrial thrombus in dogs are available. This case report describes a 14-year-old mixed-breed bitch that was presented at the clinic because of dyspnoea. The dog suffered from alopecia for about three years and displayed polyuria and polydipsia for a number of months. Clinical examination revealed intensified inspiratory and expiratory respiratory sounds and various heart sounds. Chest X-ray showed cardiomegaly (VHS 11) and a mixed bronchoalveolar lung pattern of the caudal lung. A transthoracic echocardiography was performed and showed a moderate mitral regurgitation, a highly dilated left atrium, a low-grade pulmonary insufficiency, and a minimal aortic and tricuspid insufficiency. Additionally, a free-floating ball thrombus was found in the left atrium. Hyperadrenocorticism was indicated by an ACTH stimulation test. The previous medical therapy of the referring veterinarian consisted of benazepril and furosemide and was complemented by clopidogrel. The pet owners declined any further clinical diagnostics and therapy. The dog died 19 days later. This is the first reported case of a dog with a free-floating left atrial thrombus. Specific therapeutic strategies for intracardiac thrombi in the dog are currently not available, and therefore, every patient should be treated individually.
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Lee, Eunyoung, Barbara J. Drew, Ronald H. Selvester, and Andrew D. Michaels. "Diastolic heart sounds as an adjunctive diagnostic tool with ST criteria for acute myocardial ischemia." Acute Cardiac Care 11, no. 4 (January 2009): 229–35. http://dx.doi.org/10.1080/17482940903203071.
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Stojkovic, Gabrijela, Suncica Mladenov, Dimitrije Jovanovic, Aleksandar Stankovic, Marina Deljanin-Ilic, and Arsen Ristic. "The importance of echocardiography in diagnostics of idiopathic pulmonary arterial hypertension: A case report." Srpski arhiv za celokupno lekarstvo 139, no. 5-6 (2011): 376–79. http://dx.doi.org/10.2298/sarh1106376s.
Повний текст джерелаАнотація:
Introduction. Idiopathic pulmonary arterial hypertension (IPAH) is rare and difficult progressive disease with prevalence of approximately 15 cases per million residents, with predominant female cases. Case Outline. A 47-year-old female presented with symptoms and signs of the right heart chambers failure. Over prior seven years the patient had the feeling of suffocation and fatigue when walking, and received treatment for bronchial asthma. Physical examination revealed a marked loud second heart sound over the pulmonary artery. Electrocardiogram: right ventricular hypertrophy. Spirometric (pulmonary capacity) test, cardiac perfusion scan and spiral CT scanning excluded secondary pulmonary arterial hypertension. Blood testing for connective tissue diseases and HIV were within normal reference limits. Transthoracic colour Doppler echocardiography demonstrated a mild tricuspid regurgitation with high values of estimated maximal and middle systolic pressure of the right ventricle (135/110 mm Hg), and excluded previous heart disease. Cardiac catheterization confirmed IPAH diagnosis, with systolic right ventricular pressure of 101/47/66 mm Hg and pulmonary capillary pressure of 30/13/10 mm Hg. Basic therapy with sildenafil, nevertheless, considerable limitations of strain tolerance was still present. Conclusion. IPAH is a severe heart disease with non-specific signs and symptoms. Screening for IPAH is transthoracic colour Doppler echocardiography shows high correlation with cardiac catheterization.
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Javadzadegan, Hassan, Jahan Porhomayon, Alireza Sadighi, Mehrdad Yavarikia, and Nader Nader. "Isolated Interrupted Aortic Arch: Unexpected Diagnosis in a 63-Year-Old Male." Case Reports in Critical Care 2011 (2011): 1–3. http://dx.doi.org/10.1155/2011/989621.
Повний текст джерелаАнотація:
A 63-year-old male with history of hypertension, dyspnea on exertion, and chronic chest pain was admitted for elective cardiac angiography. Arterial blood pressure was 160/90 mmHg in both arms. Femoral and popliteal pulses were extremely weak, and third (S3) and fourth (S4) heart sounds were audible. Aortography showed a mildly dilated aortic root with double brachiocephalic trunk and interruption of aortic arch at isthmus. Profuse and well-developed collaterals appeared at neck and thorax. The patient was recommended to take medical treatment for his hypertension and advanced heart failure. The aim of this paper, is to review the diagnostic and therapeutic options for treatment of the interrupted aortic arch.
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Jeong, Yoojin, Juhee Kim, Daeyeol Kim, Jinsoo Kim, and Kwangkee Lee. "Methods for Improving Deep Learning-Based Cardiac Auscultation Accuracy: Data Augmentation and Data Generalization." Applied Sciences 11, no. 10 (May 17, 2021): 4544. http://dx.doi.org/10.3390/app11104544.
Повний текст джерелаАнотація:
Cardiac auscultation is a cost-effective and noninvasive technique for cardiovascular disease detection. Recently, various studies have been underway for cardiac auscultation using deep learning, not doctors. When training a deep learning network, it is important to secure large amount of high-quality data. However, medical data are difficult to obtain, and in most cases the number of abnormal classes is insufficient. In this study, data augmentation is used to supplement the insufficient amount of data, and data generalization to generate data suitable for convolutional neural networks (CNN) is proposed. We demonstrate performance improvements by inputting them into the CNN. Our method achieves an overall performance of 96%, 81%, and 90% for sensitivity, specificity, and F1-score, respectively. Diagnostic accuracy was improved by 18% compared to when it was not used. Particularly, it showed excellent detection success rate for abnormal heart sounds. The proposed method is expected to be applied to an automatic diagnosis system to detect heart abnormalities and help prevent heart disease through early detection.
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Joshi, Shruti S., Mardi Hamra, and David E. Newby. "Diagnostic computed tomography in acute interscapular pain." Heart 106, no. 2 (December 24, 2019): 126–63. http://dx.doi.org/10.1136/heartjnl-2019-315821.
Повний текст джерелаАнотація:
Clinical introductionA man in his 60s with no medical history presented with sudden-onset, severe interscapular pain. He was in circulatory shock with a blood pressure of 65/30 mm Hg, heart rate of 115 beats per minute, respiratory rate of 32 breaths per minute and a room air oxygen saturation of 89%. Examination demonstrated weak peripheral pulses, an elevated jugular venous pressure, faint dual heart sounds, no cardiac murmurs and bilateral lung crepitations. An ECG was recorded which showed a broad QRS (figure 1A). There were no previous ECGs to compare this with. In view of his presentation with acute-onset interscapular pain, CT of the aorta was organised by the emergency department clinicians (figure 1B–D). After the CT result was obtained, the on-call cardiologist was contacted and a bedside echocardiogram performed. This demonstrated severe left ventricular systolic dysfunction with akinesia of the apex and lateral walls. The patient was then transferred to the catheter laboratory for an emergency invasive coronary angiogram.Figure 1ECG and CT images at presentation (A) 12 lead ECG. (B) Contrast enhanced CT aorta - coronal view. (C) Contrast enhanced CT aorta - axial view. (D) CT aorta showing 4 chamber view of the heart.What is the most likely diagnosis?Pulmonary embolism.Aortic dissection.Acute myocardial infarction.Cardiac tamponade.
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Hurtado-Cordovi, Jorge M., Seth Lipka, Jaspreet Singh, Ghulamullah Shahzad, and Paul Mustacchia. "Diagnostic Challenge of Hepatopulmonary Syndrome in a Patient with Coexisting Structural Heart Disease." Case Reports in Hepatology 2011 (2011): 1–3. http://dx.doi.org/10.1155/2011/386709.
Повний текст джерелаАнотація:
Hepatopulmonary syndrome (HPS) is a severe complication seen in advance liver disease. Its prevalence among cirrhotic patients varies from 4–47 percent. HPS exact pathogenesis remains unknown. Patient presents with signs/symptoms of chronic liver disease, and dypsnea of variable severity. Our patient is a 62 years old white male with a known history of chronic hepatitis C, cirrhosis, ascites, and hypothyroidism who presented to GI/liver clinic complaining of 1 episode BRBPR, and exacerbating dypsnea associated with nausea and few episodes of non-bloody vomit. Physical exam showed, icterus, jaundice, few small spider angiomas on the chest, decrease breath sounds bilateral right more than left, and mild tachycardic. Abdominal exam revealed mid-line scar, moderated size ventral hernia, distention, diffused tenderness, and dullness to percussion. Laboratory result: CBC 5.2/13.2/37.6/83, LFTs 83/217/125/5.2/4.7/7.4, Pt 22.6 INR 1.9 PTT35.4. CT scan showed liver cirrhosis, abdominal varices, and moderated ascites collection around ventral hernia. Calculated A-a gradient was 49.5. Echocardiography revealed patent foramen ovale (PFO) with predominant left to right shunt. In our case, existence of paten foramen ovale (PFO) and atelectasis precludes definitive diagnosis of HPS. Presence of cardiopulmonary shunt could be partially responsible for the patient’s dypsnea exacerbation.
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Winther, Simon, Louise Nissen, Samuel Emil Schmidt, Jelmer Sybren Westra, Laust Dupont Rasmussen, Lars Lyhne Knudsen, Lene Helleskov Madsen, et al. "Diagnostic performance of an acoustic-based system for coronary artery disease risk stratification." Heart 104, no. 11 (November 9, 2017): 928–35. http://dx.doi.org/10.1136/heartjnl-2017-311944.
Повний текст джерелаАнотація:
ObjectiveDiagnosing coronary artery disease (CAD) continues to require substantial healthcare resources. Acoustic analysis of transcutaneous heart sounds of cardiac movement and intracoronary turbulence due to obstructive coronary disease could potentially change this. The aim of this study was thus to test the diagnostic accuracy of a new portable acoustic device for detection of CAD.MethodsWe included 1675 patients consecutively with low to intermediate likelihood of CAD who had been referred for cardiac CT angiography. If significant obstruction was suspected in any coronary segment, patients were referred to invasive angiography and fractional flow reserve (FFR) assessment. Heart sound analysis was performed in all patients. A predefined acoustic CAD-score algorithm was evaluated; subsequently, we developed and validated an updated CAD-score algorithm that included both acoustic features and clinical risk factors. Low risk is indicated by a CAD-score value ≤20.ResultsHaemodynamically significant CAD assessed from FFR was present in 145 (10.0%) patients. In the entire cohort, the predefined CAD-score had a sensitivity of 63% and a specificity of 44%. In total, 50% had an updated CAD-score value ≤20. At this cut-off, sensitivity was 81% (95% CI 73% to 87%), specificity 53% (95% CI 50% to 56%), positive predictive value 16% (95% CI 13% to 18%) and negative predictive value 96% (95% CI 95% to 98%) for diagnosing haemodynamically significant CAD.ConclusionSound-based detection of CAD enables risk stratification superior to clinical risk scores. With a negative predictive value of 96%, this new acoustic rule-out system could potentially supplement clinical assessment to guide decisions on the need for further diagnostic investigation.Trial registration numberClinicalTrials.gov identifier NCT02264717; Results.
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Helman, Stephanie M., Elizabeth A. Herrup, Adam B. Christopher, and Salah S. Al-Zaiti. "The role of machine learning applications in diagnosing and assessing critical and non-critical CHD: a scoping review." Cardiology in the Young 31, no. 11 (November 2021): 1770–80. http://dx.doi.org/10.1017/s1047951121004212.
Повний текст джерелаАнотація:
AbstractMachine learning uses historical data to make predictions about new data. It has been frequently applied in healthcare to optimise diagnostic classification through discovery of hidden patterns in data that may not be obvious to clinicians. Congenital Heart Defect (CHD) machine learning research entails one of the most promising clinical applications, in which timely and accurate diagnosis is essential. The objective of this scoping review is to summarise the application and clinical utility of machine learning techniques used in paediatric cardiology research, specifically focusing on approaches aiming to optimise diagnosis and assessment of underlying CHD. Out of 50 full-text articles identified between 2015 and 2021, 40% focused on optimising the diagnosis and assessment of CHD. Deep learning and support vector machine were the most commonly used algorithms, accounting for an overall diagnostic accuracy > 0.80. Clinical applications primarily focused on the classification of auscultatory heart sounds, transthoracic echocardiograms, and cardiac MRIs. The range of these applications and directions of future research are discussed in this scoping review.
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Aziz, Sumair, Muhammad Umar Khan, Majed Alhaisoni, Tallha Akram, and Muhammad Altaf. "Phonocardiogram Signal Processing for Automatic Diagnosis of Congenital Heart Disorders through Fusion of Temporal and Cepstral Features." Sensors 20, no. 13 (July 6, 2020): 3790. http://dx.doi.org/10.3390/s20133790.
Повний текст джерелаАнотація:
Congenital heart disease (CHD) is a heart disorder associated with the devastating indications that result in increased mortality, increased morbidity, increased healthcare expenditure, and decreased quality of life. Ventricular Septal Defects (VSDs) and Arterial Septal Defects (ASDs) are the most common types of CHD. CHDs can be controlled before reaching a serious phase with an early diagnosis. The phonocardiogram (PCG) or heart sound auscultation is a simple and non-invasive technique that may reveal obvious variations of different CHDs. Diagnosis based on heart sounds is difficult and requires a high level of medical training and skills due to human hearing limitations and the non-stationary nature of PCGs. An automated computer-aided system may boost the diagnostic objectivity and consistency of PCG signals in the detection of CHDs. The objective of this research was to assess the effects of various pattern recognition modalities for the design of an automated system that effectively differentiates normal, ASD, and VSD categories using short term PCG time series. The proposed model in this study adopts three-stage processing: pre-processing, feature extraction, and classification. Empirical mode decomposition (EMD) was used to denoise the raw PCG signals acquired from subjects. One-dimensional local ternary patterns (1D-LTPs) and Mel-frequency cepstral coefficients (MFCCs) were extracted from the denoised PCG signal for precise representation of data from different classes. In the final stage, the fused feature vector of 1D-LTPs and MFCCs was fed to the support vector machine (SVM) classifier using 10-fold cross-validation. The PCG signals were acquired from the subjects admitted to local hospitals and classified by applying various experiments. The proposed methodology achieves a mean accuracy of 95.24% in classifying ASD, VSD, and normal subjects. The proposed model can be put into practice and serve as a second opinion for cardiologists by providing more objective and faster interpretations of PCG signals.
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Hamlin, Shannan K., Penelope S. Villars, Joseph T. Kanusky, and Andrew D. Shaw. "Role of Diastole in Left Ventricular Function, II: Diagnosis and Treatment." American Journal of Critical Care 13, no. 6 (November 1, 2004): 453–66. http://dx.doi.org/10.4037/ajcc2004.13.6.453.
Повний текст джерелаАнотація:
Left ventricular diastolic dysfunction plays an important role in congestive heart failure. Although once thought to be lower, the mortality of diastolic heart failure may be as high as that of systolic heart failure. Diastolic heart failure is a clinical syndrome characterized by signs and symptoms of heart failure with preserved ejection fraction (0.50) and abnormal diastolic function. One of the earliest indications of diastolic heart failure is exercise intolerance followed by fatigue and, possibly, chest pain. Other clinical signs may include distended neck veins, atrial arrhythmias, and the presence of third and fourth heart sounds. Diastolic dysfunction is difficult to differentiate from systolic dysfunction on the basis of history, physical examination, and electrocardiographic and chest radiographic findings. Therefore, objective diagnostic testing with cardiac catheterization, Doppler echocardiography, and possibly measurement of serum levels of B-type natriuretic peptide is often required. Three stages of diastolic dysfunction are recognized. Stage I is characterized by reduced left ventricular filling in early diastole with normal left ventricular and left atrial pressures and normal compliance. Stage II or pseudonormalization is characterized by a normal Doppler echocardiographic transmitral flow pattern because of an opposing increase in left atrial pressures. This normalization pattern is a concern because marked diastolic dysfunction can easily be missed. Stage III, the final, most severe stage, is characterized by severe restrictive diastolic filling with a marked decrease in left ventricular compliance. Pharmacological therapy is tailored to the cause and type of diastolic dysfunction.
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Łuczak, Mateusz, Łukasz Nowak, Joanna Chorbińska, Katarzyna Galik, Paweł Kiełb, Jan Łaszkiewicz, Andrzej Tukiendorf, et al. "Influence of Virtual Reality Devices on Pain and Anxiety in Patients Undergoing Cystoscopy Performed under Local Anaesthesia." Journal of Personalized Medicine 11, no. 11 (November 16, 2021): 1214. http://dx.doi.org/10.3390/jpm11111214.
Повний текст джерелаАнотація:
Background: Bladder cancer is one of the most common malignancies. Its diagnosis is based on transurethral cystoscopy. Virtual reality (VR) is a three-dimensional world generated through the projection of images, the emission of sounds and other stimuli. VR has been proven to be a very effective “distractor” and, thus, a useful tool in managing pain. The aim of this study was to determine whether the use of VR sets is technically feasible during the cystoscopy and whether the use of VR devices would reduce the degree of ailments associated with the procedure; Methods: The study prospectively included both men and women who qualified for rigid cystoscopy due to both primary and follow-up diagnostics. The study group underwent rigid cystoscopy with the VR set and the control group underwent the procedure without the VR set. Patients enrolled in both groups were subjected to blood pressure, heart rate and saturation measurements before, during and after the procedure. Additionally, the patients were asked to describe the severity of fear, pain sensations and nausea associated with the procedure. Non-verbal pain manifestations were assessed using the adult adjusted Faces, Legs, Activity, Cry and Consolability (FLACC) scale; Results: The study population included 103 patients (74M/29F; mean age 64.4 years). Pain intensity differed significantly between the groups, reaching lower values in the VR group. In all analyzed subgroups the use of the VR set was associated with higher levels of nausea. The mean FLACC score reached higher values for patients without the VR set. Blood pressure as well as heart rate increased during the procedure and decreased afterwards. The increase in systolic blood pressure and pulse rate was statistically higher in the control group; Conclusions: This study confirmed that cystoscopy is associated with considerable preprocedural fear and severe pain. Blood pressure and heart rate rise significantly during the cystoscopy. VR sets can lower pain perception during cystoscopy, but they may cause moderate nausea.
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Yamakawa, Nobuhide, Norihiko Kotooka, Tomoyuki Kato, Tatsuhiko Kuroda, and Koichi Node. "Cardiac acoustic biomarkers as surrogate markers to diagnose the phenotypes of pulmonary hypertension: an exploratory study." Heart and Vessels 37, no. 4 (October 1, 2021): 593–600. http://dx.doi.org/10.1007/s00380-021-01943-7.
Повний текст джерелаАнотація:
AbstractPulmonary hypertension (PH) is commonly associated with left heart disease. In this retrospective study, using the database of a clinical study conducted between January 2008 and July 2008, the phenotypes of PH were classified using non-invasive cardiac acoustic biomarkers (CABs) and compared with classification by echocardiography. Records with same-day measurement of acoustic cardiography and right heart catheterization (RHC) parameters were included; cases with congenital heart disease were excluded. Using the RHC measurements, PH was classified as pre-capillary PH (Prec-PH), isolated post-capillary PH (Ipc-PH), and combined pre-capillary and post-capillary PH (Cpc-PH). The first, second, third, and fourth heart sounds (S1, S2, S3, and S4) were quantified as CABs (intensity, complexity, and strength). Forty subjects were selected: 5 had Prec-PH, 5 had Ipc-PH, 8 had Cpc-PH, and 22 had No-PH. CABs were significantly correlated with RHC measurements, with significant differences among phenotypes. Phenotype classification was performed using various CABs, and the diagnostic performance as assessed by the area under the receiver operating characteristic curve was 0.674–0.720 for Prec-PH, 0.657–0.807 for Ipc-PH, and 0.742 for Cpc-PH. High negative and low positive predictive values for phenotype identification were observed. CABs may provide an ambulatory measurement method with home-monitoring friendliness which is more convenient than standard examinations to identify presence of PH and its phenotypes.
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Đurović, Ljiljana. "Chronic lymphocytic leukemia in general practice." Opsta medicina 27, no. 1-2 (2021): 40–46. http://dx.doi.org/10.5937/opmed2102040d.
Повний текст джерелаАнотація:
Introduction: Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults, rarely affecting children. It is more common in males over 60. Etiopathogenetically, it represents an abnormal proliferation of lymphocytes in the bone marrow, which are dysfunctional although morphologically similar to mature ones. Case report: Female patient, 66, a housewife, comes for an examination due to fatigue lasting about a month and weight loss of 3-4 kg. She denies other health problems. On the examination, she is alert, oriented to time, space, and persons, eupnoeic, lymphadenopathy on the neck, axillae and groins. She gives away the impression of a patient with mild clinical symptoms. Clinical examination: clear breath sounds in all lung fields, regular heartbeat, clear tones, BP 140/80 mmHg, abdomen at chest level, painless to palpation, liver not palpable, and spleen palpated 2 cm below the costal arch. CBC (complete blood count) showed an increased number of leukocytes 181.30x109 /L and lymphocytosis 92.2%, other parameters were normal. She was referred to the hematologist in the Kraljevo General Hospital, where further diagnostics were performed. Blood count was repeated, Chest X-ray was performed, ultrasound (US) of the abdomen neck, axillae, groins, and heart, virology tests, ENT examination. Abdominal US showed a pathological finding with enlarged liver, spleen, lymph nodes (LN). ENT examination: enlarged tonsils, other findings unremarkable. Since chronic lymphocytic leukemia was suspected, she was referred to the Clinical Center of Serbia. Immunophenotyping (IF) and computed tomography (CT) of the neck, chest, and abdomen were performed. The diagnosis of CLL was confirmed. A Medical Council decided to perform immunochemotherapy (IHT) with fludarabine and rituximab. After 6 received cycles, the patient feels well and the CBC parameters are normal. Conclusion: CLL may be asymptomatic or nonspecific and with mild symptoms in a large number of patients. Therefore, blood tests with leukocytosis and absolute lymphocytosis findings are crucial to suspect the disease and perform further diagnostics.
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Oliynik, V. N. "A statistical algorithm for fast estimation of heart rate and localization of cardiac sounds in phonocardiograms recorded by electronic stethoscopes." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 3 (2021): 81–84. http://dx.doi.org/10.17721/1812-5409.2021/3.14.
Повний текст джерелаАнотація:
A draft version of the algorithm for fast determination of duration of the systolic and diastolic phases of the cardiac cycle based on a statistical analysis of a digital phonocardiogram is presented. The developed technique includes localization of the cardiac tones in the record by a quantile dichotomy and modal analysis of the calculated time intervals between the adjacent detected peaks. Next, the scatter plot is constructed in terms of time intervals before and after each peak. The stability of the cardiac rhythm is determined by the density of the cluster occurring near the cross-section of two modal values plotted along the axes. At dominance of a cardiac component in the signal, the discussed approach allows quite reliable determination of the moments of the emergence of the first and second cardiac sounds tones practically on each of the cardiac cycles. This opens the possibility to analyze the variation in the duration of separate phases of heart contractions over time. Due to the work directly in the time domain and low computational costs, the algorithms of this class are suitable for application in portable diagnostic systems with limited processor power.
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Vörös, Károly, Ingo Nolte, Stephan Hungerbühler, Jenő Reiczigel, Jan Ehlers, Guy Tater, Reinhard Mischke, Tanja Zimmering, and Matthias Schneider. "Sound recording and digital phonocardiography of cardiac murmurs in dogs by using a sensor-based electronic stethoscope." Acta Veterinaria Hungarica 59, no. 1 (March 1, 2011): 23–35. http://dx.doi.org/10.1556/avet.59.2011.1.3.
Повний текст джерелаАнотація:
The goals of this study were to present a technique of digitalised sound recordings and phonocardiograms (dPCGs), and to analyse its diagnostic capabilities. Heart sounds of 20 dogs were auscultated in vivo (on-line) and recorded with dPCGs by two authors using a Welch Allyn Meditron Stethoscope System. Sound recordings were auscultated off-line and blindly by four different observers having various auscultatory experiences, then listened to while viewing dPCGs. The results were compared to echocardiographic diagnoses. There was a significant agreement (p < 0.001) between on-line and off-line auscultatory findings regarding the four observers, ranging from 45% to 75% (weighted kappa values: 0.72 to 0.87). The best agreement was achieved by Observer 1 having the highest experience. Significant differences (p < 0.05) were found between Observer 1 and Observer 4 (with the lowest experience) in judging the quality of the murmurs during the off-line and blind auscultation. However, there were only minimal differences (95% to 100% agreements) in dPCG analyses among the four observers regarding intensity and quality of the murmurs while simultaneously listening to and viewing the dPCGs. Significant correlations were found between the traditional ‘0 to 6 scale’ and a new ‘0 to 3 scale’ murmur intensity gradings by all observers (correlation coefficients 0.640 to 0.908; p < 0.01 to p < 0.001). Analysis of dPCGs might be a valuable, additional tool helping with the diagnosis of canine cardiac murmurs, especially for those with less cardiological experience.
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Elhanafy, Mohamed M., and Dennis D. French. "Atypical Presentation of Constrictive Pericarditis in a Holstein Heifer." Case Reports in Veterinary Medicine 2012 (2012): 1–5. http://dx.doi.org/10.1155/2012/604098.
Повний текст джерелаАнотація:
The field diagnosis of constrictive pericardial effusion is often established on the pertinent pathognomonic physical examination findings, but the condition cannot be ruled out based on absence of these cardinal signs. Constrictive pericardial effusion is not always manifested by bilateral jugular venous distention and pulsation, brisket edema, and muffled heart sounds, all of which are considered the key points in the field diagnosis of pericardial effusion and hardware disease. This case will also document that the outcomes of hematology, serum biochemistry panels, and blood gas analysis can be totally inconsistent with passive venous congestion and constrictive pericardial effusion in cattle. Chest radiographic findings revealed radio dense, wire-like objects; the findings were suggestive but not conclusive for pericardial or pleural effusions, due to indistinguishable diaphragmatic outline and cardiopulmonary silhouette. Cardiac ultrasonography was found to be an excellent paraclinical diagnostic procedure for cases that potentially have traumatic pericarditis and constrictive pericardial effusion. Ultrasound-guided pericardiocentesis was also a valuable diagnostic aid in establishing a definitive diagnosis.
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Gradolewski, Dawid, Giovanni Magenes, Sven Johansson, and Wlodek Kulesza. "A Wavelet Transform-Based Neural Network Denoising Algorithm for Mobile Phonocardiography." Sensors 19, no. 4 (February 24, 2019): 957. http://dx.doi.org/10.3390/s19040957.
Повний текст джерелаАнотація:
Cardiovascular pathologies cause 23.5% of human deaths, worldwide. An auto-diagnostic system monitoring heart activity, which can identify the early symptoms of cardiac illnesses, might reduce the death rate caused by these problems. Phonocardiography (PCG) is one of the possible techniques able to detect heart problems. Nevertheless, acoustic signal enhancement is required since it is exposed to various disturbances coming from different sources. The most common denoising enhancement is based on the Wavelet Transform (WT). However, the WT is highly susceptible to variations in the noise frequency distribution. This paper proposes a new adaptive denoising algorithm, which combines WT and Time Delay Neural Networks (TDNN). The acquired signal is decomposed by means of the WT using the coif five-wavelet basis at the tenth decomposition level and then provided as input to the TDNN. Besides the advantage of adaptive thresholding, the reason for using TDNNs is their capacity of estimating the Inverse Wavelet Transform (IWT). The best parameters of the TDNN were found for a NN consisting of 25 neurons in the first and 15 in the second layer and the delay block of 12 samples. The method was evaluated on several pathological heart sounds and on signals recorded in a noisy environment. The performance of the developed system with respect to other wavelet-based denoising approaches was validated by the online questionnaire.
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Stefanović, Ivana, Vlada Tamburkovski, Jelena Kašćak, and Slađana Anđelić. "ECG findings in pulmonary embolism or the pseudoinfarction pattern." Halo 194 27, no. 3 (2021): 91–95. http://dx.doi.org/10.5937/halo27-34539.
Повний текст джерелаАнотація:
Introduction/Objective: A diagnosis of STEMI can be made for patients with persistent chest discomfort or other symptoms of ischemia and an ST-segment elevation in at least two adjoining ECG leads. The differential diagnosis of ST-segment elevation consists of 4 major conditions: myocardial infarction, pericarditis, early repolarization syndrome, secondary changes and other diagnoses, such as pulmonary embolism (PE). The dilemma is whether an ST-elevation always requires the PPCI protocol to be activated? The objective of this article is to acquaint medical doctors with other similar clinical presentations and the importance of making the right decision that directly affects the course of treatment and the outcome for the patient. Case report: An 84-year-old woman called the EMS hotline complaining of chest pain and breathing difficulty. She was found in aprone position on a flat surface, pale and covered in sweat, but without chest pain at the ti. She had had hip replacement surgery and was discharged from the hospital two days earlier. She was currently receiving 0.4ml of Fraxiparine daily. Her blood pressure was 90/60mmHg, heart rate 115 per minute, breathing frequency 20 breaths per minute, blood oxygen saturation 70%. Upon auscultation, her heart sounds were softer, breathing was normal with no wheezing or crackles. ECG: ST-segment elevation in leads II, III and avF and reciprocal ST-segment depression in leads I, avL and V2-V6 and an S1Q3T3 pattern. Conclusion: There are many articles describing cases where the PPCI protocol had been activated for patients with similar ECG findings and who had been subjected to emergency coronary angiography. Since the coronary angiography findings had been normal and they were transferred for further diagnostics. Coronary angiography per se will not harm these patients, but delaying adequate treatment for pulmonary embolism could have a lethal effect. This is why it is very important to record serial ECG tracings. Rapid regression of ECG findings and Q-wave regression favorises pulmonary embolism.
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Gevorgyan, S. G., A. S. Khachunts, G. S. Gevorgyan, A. A. Tumanian, and N. E. Tadevosyan. "Applicability of the single-layer flat-coil-oscillator technology-based vibration and vibro-acoustic sensors in medical and biological study of the cardiovascular system: Advantages and perspectives of the carotid pulse wave registration." Review of Scientific Instruments 93, no. 5 (May 1, 2022): 054109. http://dx.doi.org/10.1063/5.0076197.
Повний текст джерелаАнотація:
The possibility and feasibility of using the single-layer flat-coil-oscillator (SFCO) technology-based vibration and vibro-acoustic sensors in diagnostic devices and biomedical studies of the cardiovascular system are discussed in this paper. Using an example of recording pulse waves of left carotid artery and their analysis, the information content of the data recorded by these sensors in a number of cases is shown—assessment of age-related changes in the stiffness of the vascular wall, assessment of the dynamics of systolic volume, reflecting myocardial contractility, and rhythm disturbance (extra-systole and arrhythmia). These sensors are shown to be promising in recording heart sounds due to their high sensitivity. The possibility of assessing the dynamics of relaxation of the cardiovascular system after exercise ( stress test) is shown. The advantages of using SFCO vibration and vibro-acoustic sensors are high sensitivity, ease of use, and no need to train specialists. These advantages open new perspectives for their implementation in mobile wearable “smart” devices for individual monitoring.
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Kittleson, Mark D., and Etienne Côté. "The Feline Cardiomyopathies: 1. General concepts." Journal of Feline Medicine and Surgery 23, no. 11 (October 25, 2021): 1009–27. http://dx.doi.org/10.1177/1098612x211021819.
Повний текст джерелаАнотація:
Practical relevance: The feline cardiomyopathies are the most prevalent type of heart disease in adult domestic cats. Several forms have been identified (see Parts 2 and 3), with hypertrophic cardiomyopathy (HCM) being the most common. Clinically the cardiomyopathies are often indistinguishable. Cats with subclinical cardiomyopathy may or may not have characteristic physical examination findings (eg, heart murmur, gallop sound), or radiographic cardiomegaly. Cats with severe disease may develop signs of heart failure (eg, dyspnea, tachypnea) or systemic arterial thromboembolism (ATE; eg, pain and paralysis). Sudden death is possible. Treatment usually does not alter the progression from subclinical to clinical disease and often the treatment approach, once clinical signs are apparent, is the same regardless of the type of cardiomyopathy. However, differentiating cardiomyopathy from normal variation may be important prognostically. Patient group: Domestic cats of any age from 3 months upward, of either sex and of any breed, can be affected. Mixed-breed cats are most commonly affected but certain breeds are disproportionately prone to developing HCM. Diagnostics: Subclinical feline cardiomyopathies may be suspected based on physical examination findings, thoracic radiographs and cardiac biomarker results but often the disease is clinically silent. The definitive clinical confirmatory test is echocardiography. Left heart failure (pulmonary edema and/or pleural effusion) is most commonly diagnosed radiographically, but point-of-care ultrasound and amino terminal pro-B-type natriuretic peptide (NT-proBNP) biomarker testing can also be useful, especially when the stress of taking radiographs is best avoided. Key findings: Knowledge of pathophysiological mechanisms helps the practitioner identify the feline cardiomyopathies and understand how these diseases progress and how they manifest clinically (heart failure, ATE). Existing diagnostic tests have strengths and limitations, and being aware of these can help a practitioner deliver optimal recommendations regarding referral. Conclusions: Several types of feline cardiomyopathies exist in both subclinical (mild to severe disease) and clinical (severe disease) phases. Heart failure and ATE are the most common clinical manifestations of severe cardiomyopathy and are therapeutic targets regardless of the type of cardiomyopathy. The long-term prognosis is often guarded or poor once overt clinical manifestations are present. Areas of uncertainty: Some cats with presumed cardiomyopathy do not have echocardiographic features that fit the classic cardiomyopathies (cardiomyopathy – nonspecific phenotype). Although no definitive treatment is usually available, understanding how cardiomyopathies evolve remains worthy of investigation.
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Treadway, Katharine. "Heart Sounds." New England Journal of Medicine 354, no. 11 (March 16, 2006): 1112–13. http://dx.doi.org/10.1056/nejmp058202.
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Huffman, Lisa M. "Heart sounds." Nursing Made Incredibly Easy! 10, no. 2 (2012): 51–54. http://dx.doi.org/10.1097/01.nme.0000411098.98692.72.
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Martin, Lee. "Heart Sounds." River Teeth: A Journal of Nonfiction Narrative 16, no. 1 (2014): 31–46. http://dx.doi.org/10.1353/rvt.2014.0022.
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Cheng, Tsung O. "Heart sounds." International Journal of Cardiology 135, no. 3 (July 2009): 405. http://dx.doi.org/10.1016/j.ijcard.2008.02.018.
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Mehta, Nishita A., and Michelle N. Fonseca. "A rare case of abdominal pregnancy: diagnostic and therapeutic challenges." International Journal of Reproduction, Contraception, Obstetrics and Gynecology 9, no. 3 (February 27, 2020): 1288. http://dx.doi.org/10.18203/2320-1770.ijrcog20200918.
Повний текст джерелаАнотація:
Abdominal pregnancy refers to a pregnancy that has implanted in the abdominal cavity, the estimated incidence being 1 per 30,000 births. A 36-year-old primigravida with term pregnancy with fetal demise was referred to us. Examination was suggestive of single foetus of 30 weeks’ gestation with longitudinal lie and cephalic presentation with absent foetal heart sounds. The cervical os was closed, uneffaced. Ultrasound done at 18 weeks’ gestation had reported pregnancy in a bicornuate uterus. Present ultrasound revealed intrauterine foetal demise of 28.4 weeks. Cervical ripening, done using prostaglandins, mechanical dilation with Foley’s catheter and oxytocin, had failed, and thus patient was taken up for surgery. Findings revealed an abdominal pregnancy with a macerated fetus of 1070 grams (severely growth restricted). Placenta was found to be implanted on multiple areas of both small and large intestine and posterior peritoneum. Placenta was left in situ. Postoperative recovery was uneventful. She was given higher antibiotics, 4 doses of tablet mifepristone 200 mg and monitored regularly with ultrasound/ MRI and bHCG which showed slow placental resorption. Conclusion- Abdominal pregnancies, associated with a high maternal and perinatal morbidity and mortality, are diagnosed preoperatively only in 45% of cases. Thus, a high index of suspicion and improvement in diagnosis is the need of the hour. Successful management includes prompt intraoperative recognition and management of the placenta (we advocate leaving the placenta in situ), multidisciplinary approach with involvement of surgeons and interventional radiologists, access to blood products, meticulous postoperative care and close observation during the subsequent delayed reabsorption.
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Tack, Bieke, Daniel Vita, Irène Mansosa, Thomas Nsema Mbaki, Naomie Wasolua, Aimée Luyindula, Jaan Toelen, Octavie Lunguya, and Jan Jacobs. "Field Experiences with Handheld Diagnostic Devices to Triage Children under Five Presenting with Severe Febrile Illness in a District Hospital in DR Congo." Diagnostics 12, no. 3 (March 18, 2022): 746. http://dx.doi.org/10.3390/diagnostics12030746.
Повний текст джерелаАнотація:
As part of a field study (NCT04473768) in children presenting with severe febrile illness to Kisantu hospital (DR Congo), we retrospectively compiled user experiences (not performance) with handheld diagnostic devices assisting triage: tympanic thermometer, pulse oximeter (measuring heart rate, respiratory rate and oxygen saturation), hemoglobinometer and glucometer. Guidance documents for product selection were generic and scattered. Stock rupture, market withdrawal and unaffordable prices interfered with procurement. Challenges at implementation included environmental temperature, capillary blood sampling (antisepsis, order of multiple tests, filling microcuvettes and glucose strips), calibration (environmental temperature, cold chain) and liability-oriented communication with a manufacturer. Instructions for use were readable and contained symbol keys; two devices had printed French-language instructions. Shortcomings were poor integration of figures with text and distinct procedures for the oximeter and its sensor. Usability interview revealed appreciations for quick results, visibility of the display and memory function (three devices) but also problems of capillary blood sample transfer, cleaning, too long of a time-to-results (respiratory rate) and size, fitting and disposal of thermometer probes. Pictorial error messages were preferred over alphanumeric error codes but interpretation of symbols was poor. Alarm sounds of the oximeter caused unrest in children and caretakers perceived the device as associated with poor prognosis.
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Sriraman, Gurumani, Valli Rajasekaran, and Roopak Visakan Raja. "An atypical case of Kartagener’s syndrome." International Journal of Otorhinolaryngology and Head and Neck Surgery 4, no. 1 (December 22, 2017): 281. http://dx.doi.org/10.18203/issn.2454-5929.ijohns20175643.
Повний текст джерелаАнотація:
<p class="abstract"><span lang="EN-IN">Kartagener’s syndrome is an autosomal recessive disease characterized by the tetrad of situs inversus, bronchiectasis, sinusitis and infertility. It is a subset of a larger group of disease known as primary ciliary dyskinesia. A 23 year old male patient presented to our hospital with complaints of Right sided headache for the past 3 weeks. General Physical examination was normal except that the heart sounds were heard over the right side. Dextrocardia was suspected. Routine ENT and Diagnostic nasal endoscopy examination revealed deviated septum towards the left along with pale greyish polyp like mass in the right nasal cavity. CT PNS was ordered. It showed bilateral frontal, ethmoidal and maxillary sinusitis with Right nasal polyp. Routine Blood investigations were normal but Chest X-ray showed dextrocardia with fundal shadow over the right side and normal ECG was obtained only when the chest leads were reversed. USG abdomen confirmed the suspicion of situs inversus totalis. To rule out Kartageners syndrome HRCT Chest was done which revealed normal lungs with no findings. Sperm analysis was also done which was normal except for the count (<15 million/ml). Saccharin test was performed and it was delayed (>20 min). Anesthetic fitness was obtained and he was taken up for surgery - Septoplasty with fess.<em> </em>The diagnosis of kartageners syndrome was done based on clinical and radiological findings, with variation in form of no bronchiectasis and oligospermia. This type of atypical presentation of Kartagener’s syndrome might be a rare sub type of the disease which is infrequently reported.</span></p>
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TAYLOR, DOLORES LAKE. "ASSESSING HEART SOUNDS." Nursing 15, no. 1 (January 1985): 51–53. http://dx.doi.org/10.1097/00152193-198501000-00011.
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Pechetty, Ramya, and Lalita Nemani. "Additional Heart Sounds—Part 1 (Third and Fourth Heart Sounds)." Indian Journal of Cardiovascular Disease in Women WINCARS 5, no. 02 (June 2020): 155–64. http://dx.doi.org/10.1055/s-0040-1713828.
Повний текст джерелаАнотація:
AbstractS3 is a low-pitched sound (25–50Hz) which is heard in early diastole, following the second heart sound. The following synonyms are used for it: ventricular gallop, early diastolic gallop, protodiastolic gallop, and ventricular early filling sound. The term “gallop” was first used in 1847 by Jean Baptiste Bouillaud to describe the cadence of the three heart sounds occurring in rapid succession. The best description of a third heart sound was provided by Pierre Carl Potain who described an added sound which, in addition to the two normal sounds, is heard like a bruit completing the triple rhythm of the heart (bruit de gallop). The following synonyms are used for the fourth heart sound (S4): atrial gallop and presystolic gallop. S4 is a low-pitched sound (20–30 Hz) heard in presystole, i.e., shortly before the first heart sound. This produces a rhythm classically compared with the cadence of the word “Tennessee.” One can also use the phrase “A-stiff-wall” to help with the cadence (a S4, stiff S1, wall S2) of the S4 sound.